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Method for calculating characteristic value and characteristic vector of flexible body point distribution model based on interpolation algorithm

A technology of point distribution model and calculation method, applied in calculation, 3D modeling, image analysis, etc., can solve the problems of inability to form real-time distribution model, poor model accuracy, and poor practicability.

Inactive Publication Date: 2010-02-03
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the deficiencies of existing flexible body point distribution models that cannot form real-time distribution models, poor model accuracy, and poor practicability, the present invention provides an intermediate transition model that can form real-time distribution, high model accuracy, and good practicability based on Calculation method of eigenvalue and eigenvector of flexible body point distribution model based on interpolation algorithm

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  • Method for calculating characteristic value and characteristic vector of flexible body point distribution model based on interpolation algorithm
  • Method for calculating characteristic value and characteristic vector of flexible body point distribution model based on interpolation algorithm
  • Method for calculating characteristic value and characteristic vector of flexible body point distribution model based on interpolation algorithm

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[0163] The present invention will be further described below in conjunction with the accompanying drawings.

[0164] refer to Figure 1 to Figure 5 , a method for calculating eigenvalues ​​and eigenvectors of a flexible body point distribution model based on an interpolation algorithm, characterized in that: the calculation method includes the following steps:

[0165] 1), load two adjacent time T a and T b The flexible body distribution model M a and M b , whose calculation formula is:

[0166] m a =a , Φ a ,λ a >, M b =b , Φ b ,λ b >

[0167] 2), through the flexible body distribution model M a and M b , respectively compute the mean shape y a and y b , eigenmatrices Φa and Φb, and eigenvalues ​​λ a and lambda b , set the flexible body from T a to T b is continuously changing,

[0168] 2.1) Calculation of the eigenvalues ​​of the intermediate model:

[0169] lambda t ≈a 2 lambda a +b 2 lambda b , (25)

[0170] Here λa and λb are the eigenvalue vect...

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Abstract

The invention relates to a method for calculating characteristic values and characteristic vectors of a flexible body point distribution model based on an interpolation algorithm, comprising the following steps: (1) loading flexible distribution models Ma and Mb of two adjacent times Ta and Tb, wherein Ma=<gamma a, phi a and lambada a>, Mb=<* b, phi b and lambada b>; (2) respectively calculating average shapes * a and * b, characteristic matrixes phi a and phi b and characteristic values lambada a and lambada b by the flexible body distribution models Ma and Mb to set the continuous change ofa flexible body from the Ta to the Tb; (2.1) calculating the characteristic value of a middle model; and (2.2) estimating a characteristic vector of the middle model. The method can form middle transition models which are distributed in real time and has high model accuracy and good practicality.

Description

technical field [0001] The invention relates to a point distribution model analysis technology of a flexible body, which combines graphics, matrix theory, linear algebra, medical image analysis, computer image processing technology and a parameter calculation method of a flexible body model. Background technique [0002] Compared with rigid bodies, it is more complicated to model and analyze flexible bodies in the computer. In real life, it is very common for objects to change flexibly over time, such as literature 1: Wang Minqin, Korea Qiangtu, Yongqiu. Medical images based on deformation models Segmentation review [J]. Medical and Health Equipment, 2009, 30(2): -37-39; Literature 2 "Munsell, B.C.; Dalal, P.; Song Wang, "Evaluating Shape Correspondence for Statistical Shape Analysis: A Benchmark Study," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, no.11, pp.2023-2039, Nov.2008, E. Marcel, B.C; Della, P.; Wang Song, "Shape Matching in Statistical S...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06T7/00
Inventor 陈胜勇杜雅慧管秋毛国红王万良
Owner ZHEJIANG UNIV OF TECH
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